Personal devices, such as computers, phones, personal digital assistants and the like have gained wide popularity in recent years. As technology improves, these devices have become increasingly smaller in size and highly portable. In fact, wireless, portable devices of various types now commonly communicate with one another allowing users flexibility of use and facilitating data, voice and audio communication. To this end, networking of mobile or portable and wireless devices is required.
With regard to the wireless networking of personal devices, a particular modem, namely modems adapted to the up-coming IEEE 802.11n and 802.11ac industry standard, are anticipated to be commonly employed. These and similar standards allow an array of antennas is placed inside or nearby the personal device and a radio frequency (RF) semiconductor device receives signal or data through the array and an analog-to-digital converter, typically located within the personal device, and converts the received signal to baseband range. Thereafter, a baseband processor is employed to process and decode the received signal to the point of extracting raw data, which may be files transferred remotely and wireless, from another personal device or similar equipment with the use of a transmitter within the transmitting PC.
To do so, pointing of the array of antennas, which is essentially multiple antennas, hence the name multi-input-multi-output (MIMO), to the desired location to maximize reception and transmission quality is an issue. For example, data or information rate throughput, signal reception and link range are improved. The latest IEEE802.11n/ac standards currently being developed include advanced multi-antenna techniques in order to process parallel data streams simultaneously in order to increase throughput capability, and improve link quality by “smartly” transmitting and receiving the RF signals.
There are two basic types of beamforming specified in the current 802.11n standard: explicit and implicit. For explicit beamforming the receiver measures the channel between the transmitter and receiver and sends this information, called channel state information or CSI, back to the transmitter. The transmitter can then use the channel information to calculate the best transmit “paths” or “directions” for that particular client for transmitting future packets. Using the CSI in this way is sometimes referred to as beamforming. While this method provides a direct measure of the channel for beamforming, it requires CSI to be sent over the link resulting in network overhead that can lead to reduced overall throughput.
The second basic method of beamforming, implicit beamforming, does not require CSI to be sent back to the transmitter on a packet-by-packet basis. Instead the implicit method relies on the principle of channel reciprocity. Channel reciprocity assumes that the upstream and downstream channels are essentially the same (to within a transpose operation and some trivial phase rotations), so that the receiver can use the measured channel information to beamform packets of information back to the transmitter. In this way, no explicit CSI is required to be sent over the link, thereby eliminating network overhead. The downside of implicit beamforming is that it requires a calibration procedure between the transmitter and receiver to ensure that reciprocity is achieved. The calibration procedure requires complex coordination between the access point (AP) and clients in which large amounts of CSI are periodically exchanged. An AP is a device that is wirelessly transmitting or receiving within a network of devices.
In a wireless channel, multi-path results in channel nulls. For an OFDM system, this would result in different tones having an SNR dependent on the channel strength. In a MIMO channel, there will be cross-correlation between the antennas (and transmitted streams). Depending on the type of receiver (ZF/MLD), it may result in loss of performance. Beamforming helps in removing this cross-correlation and reducing the cost of the receiver for optimal performance. However, the disparity between the streams and tones (within a stream) still exists and this affects performance.
Accordingly, what is desired is to provide a system and method that overcomes the above issues. The present invention addresses such a need.